Practical Web Analytics for User Experience How Analytics Can Help You Understand Your Users Michael Beasley UX Designer, ITHAKA Ypsilanti, Michigan, USA üf IBs fmij ELSEVIER Amsterdam Boston Heidelberg London New York Oxford M< Paris San Diego San Francisco Singapore Sydney Tokyo Morgan Kaufmann is an imprint of Elsevier
Contents ACKNOWLEDGMENTS ABOUT THE AUTHOR xiii xv CHAPTER 1 Introduction 1 What Is Web Analytics? 2 User Experience and Web Analytics Questions 3 Web Analytics and User Experience: A Perfect Fit 3 About This Book 4 Part 1: Introduction to Web Analytics 4 Part 2: Learning About Users through Web Analytics 4 Part 3: Advanced Topics 5 Google Analytics 6 Part 1 Introduction to Web Analytics 9 CHAPTER 2 Web Analytics Approach 11 Introduction 11 Get to Know Your Website 11 A Model of Analysis 14 Pose the Question 15 Gather Data 16 Transform Data 16 Analyze 16 Answer the Question 17 Balancing Time and the Need for Certainty 17 Showing Your Work 18 Context Matters 18 Data Over Time 19 Proportion is Key 20 Sometimes the Data Contradict You 22 Sometimes the Answer is "No" 22 v
Make Your Findings Repeatable 22 Key Takeaways 23 CHAPTER 3 How Web Analytics Works 25 Introduction 25 Log File Analysis 25 Page Tagging 26 Cookies 27 Accuracy 28 Accounts and Profiles 29 Click Analytics 30 Metrics and Dimensions 31 Visits 32 Unique Visitors (Metric) 32 Pageviews (Metric) 34 Pages/Visit (Metric) 35 Average Visit Duration 35 Bounce Rate (Metric) 36 % New Visits (Metric) 36 Using These Metrics 37 Interacting With Data In Google Analytics 37 Plot Rows 39 Secondary Dimension 39 Sort Type 39 Search 41 Beyond Tables 43 Key Takeaways 47 CHAPTER 4 Goals 49 Introduction 49 What are Goals and Conversions? 49 Unfortunate Colliding Terms 51 All Websites Should Have Goals 51 Why Do Goals Matter for User Experience? 51 Conversion Rate 52 Goal Reports in Google Analytics 53 Goal URLs 58 Reverse Goal Path 58 Funnel Visualization Report 60 Goal Flow 61 E-commerce 62 Multichannel Funnels 62
Part 2 When Do You Use These Reports? 63 Finding the Right Things to Measure as Key Performance Indicators 63 What Should You Measure? 64 Do Users Want To Do These Things? 69 What Can You Measure on a Website that Can Constitute a Goal? 69 Reaching a Specific Page 70 On-Page Action 71 Engagement 72 Going Beyond the Website 72 Tying It Together 73 Key Takeaways 74 Learning about Users through Web Analytics 75 CHAPTER 5 Learning about Users 77 Introduction 77 Visitor Analysis 78 Demographics Location 78 Behavior New vs. Returning 79 Behavior Frequency & Recency 79 Behavior Engagement 80 Technology Browser & OS 81 Mobile Overview 81 Custom (As in Custom Variables) 81 Key Takeaways 82 CHAPTER 6 Traffic Analysis: Learning How Users Got to Your Website 83 Introduction 83 Source and Medium (Dimensions) 83 Organic Search 85 Why Analyze Keywords? 87 Search Query Analysis 89 Exporting the Data 90 Create Candidate Categories 92 Processing the Data 93 Analyzing the Data Again 96 Basic Keyword Analysis 98 Export the Data 98
Categorize the Keywords 98 Compare Metrics 99 Referral Traffic 99 Direct Traffic 102 Paid Search Keywords 103 Key Takeaways 104 CHAPTER 7 Analyzing How People Use Your Content 105 Introduction 105 Website Content Reports 105 High Pageviews/Low Pageviews 107 Page views are Much Higher than Unique Pageviews..109 Low Time on Page 110 High Time on Page 112 High Entrances to Unique Pageviews Ratio 112 High Bounce Rate 113 High % Exit 114 Page Value 114 Comparing Page Metrics to Similar Pages 115 More Reports 116 Key Takeaways 120 CHAPTER 8 Click-Path Analysis 121 Introduction 121 Focus on Relationships between Pages 122 Navigation Summary 123 "Visitors Flow" Report 126 Analyzing How Users Move from One Page Type to Another 128 An Example: AwesomePetToys.com 129 Key Takeaways 134 CHAPTER 9 Segmentation 135 Introduction 135 Why Segment Data? 135 How To Segment Data 140 Google Analytics' Advanced Segments 142 What are the Ways You Can Segment Data? 145 AND, OR, and Sequence of Filters 145 Metrics 145 Dimensions 146 Useful Ways to Segment for UX Questions 147 Segmenting According to a Page 147 V
Segmenting According to User Traits 150 Segmenting According to Information Need 150 Whether or Not Users Completed a Goal 152 What Pages Users Landed On 152 What Pages Users Viewed/Didn't View 153 The Tip of the Iceberg 154 Key Takeaways 154 CHAPTER 10 Pairing Analytics Data with UX Methods 157 Introduction 157 Personas 157 Segmenting Based on Personas 157 Building Better Personas 161 Usability Testing 162 Test Planning 162 Test Analysis 164 Usability Test Reports 165 Usability Inspection 166 Identifying Potential Problems 167 Evidence for Problems 167 Design and Design Objectives 167 How Much Will You Improve a Number? 169 Key Takeaways 169 CHAPTER 11 Measuring the Effects of Changes 171 Introduction 171 Reframe as a Rate 172 Choose What to Measure 172 Choose When to Measure 173 Types of Changes 174 Conversion Rate 174 Redirect Traffic 176 Time on Page and Other Continuous Metrics 179 Changing Many Things at Once 180 Reporting 182 New Designs Don't Always Work 183 Key Takeaways 183 Advanced Topics 185 CHAPTER 12 Measuring Behavior within Pages 187 Introduction 187 Google Analytics In-Page Analytics 187
Click Analytics Tools 189 Making Clicks Measureable in Page Tagging Analytics Tools 190 Defining Events 191 Putting It Together 193 Analyzing Event Data 194 Pages and Events What Happened Where? 195 Making Rates 198 Segmentation 198 Virtual Pageviews 199 Key Takeaways 199 CHAPTER 13 A/B Testing 201 Introduction 201 Designing An Experiment 201 Select a Page That You Wish to Improve 201 Determine a Metric for Judging Improvement 202 Design One or More Alternatives 202 Tracking Code 203 Tools 203 Estimating the Length of a Test 205 Monitoring and "Winning" 205 Ending a Test Early 206 Key Takeaways 207 CHAPTER 14 Analytics Profiles 209 Introduction 209 Profiles 209 What are Profile Filters? 210 Making URLs Easier to Read 211 Easier Click-path Analysis by Combining Pages 212 A Profile for UX Data 213 Key Takeaways 213 CHAPTER 15 Regular Reporting and Talking to Stakeholders 215 Introduction 215 Reporting Culture 215 Why You Report Analytics Data 216 Why You Monitor Analytics Data 217 Choosing Metrics to Report 218 Reporting Frequency 220 Keep It Concise 220
.. - ' Making the Case for Usability Activities 221 Making the Case for Design Changes 221 Making the Case for User Research 224 KeyTakeaways 224 CHAPTER 16 Web Analytics in the Near Future 227 Introduction 227 Mobile Application Analytics 227 Cross-Device Measurement 228 Better Measurement of On-Page Behavior 228 Connecting to Other Data Sources 228 The Continuing Dominance of Google 229 Things Will Keep Changing 229 INDEX 231